Abstract

A well known problem in peer-to-peer overlays is that no single entity has control over the software,
hardware and configuration of peers. Thus, each peer can selfishly adapt its behaviour to maximise its
benefit from the overlay. This thesis is concerned with the modelling and design of incentive mechanisms
for QoS-overlays: resource allocation protocols that provide strategic peers with participation incentives,
while at the same time optimising the performance of the peer-to-peer distribution overlay.
The contributions of this thesis are as follows. First, we present PledgeRoute, a novel contribution
accounting system that can be used, along with a set of reciprocity policies, as an incentive mechanism
to encourage peers to contribute resources even when users are not actively consuming overlay services.
This mechanism uses a decentralised credit network, is resilient to sybil attacks, and allows peers to
achieve time and space deferred contribution reciprocity. Then, we present a novel, QoS-aware resource
allocation model based on Vickrey auctions that uses PledgeRoute as a substrate. It acts as an incentive
mechanism by providing efficient overlay construction, while at the same time allocating increasing
service quality to those peers that contribute more to the network. The model is then applied to lagsensitive
chunk swarming, and some of its properties are explored for different peer delay distributions.
When considering QoS overlays deployed over the best-effort Internet, the quality received by a
client cannot be adjudicated completely to either its serving peer or the intervening network between
them. By drawing parallels between this situation and well-known hidden action situations in microeconomics,
we propose a novel scheme to ensure adherence to advertised QoS levels. We then apply
it to delay-sensitive chunk distribution overlays and present the optimal contract payments required,
along with a method for QoS contract enforcement through reciprocative strategies. We also present a
probabilistic model for application-layer delay as a function of the prevailing network conditions.
Finally, we address the incentives of managed overlays, and the prediction of their behaviour. We
propose two novel models of multihoming managed overlay incentives in which overlays can freely
allocate their traffic flows between different ISPs. One is obtained by optimising an overlay utility
function with desired properties, while the other is designed for data-driven least-squares fitting of the
cross elasticity of demand. This last model is then used to solve for ISP profit maximisation.